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- An exponential random variable is a continuous random variable that has a probability density function of the form f(x) = λe^(-λx), where λ is the rate parameter1. The mean of an exponential random variable is the inverse of the rate parameter, i.e. E[X] = 1/λ12. This means that the average time or distance between events is equal to 1/λ2.Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.
The continuous random variable, say X is said to have an exponential distribution, if it has the following probability density function: λ is called the distribution rate. The mean of the exponential distribution is calculated using the integration by parts. Hence, the mean of the exponential distribution is 1/λ.
byjus.com/maths/exponential-distribution/The mean or expected value of an exponentially distributed random variable X with rate parameter λ is given by E [ X ] = 1 λ . {\displaystyle \operatorname {E} [X]={\frac {1}{\lambda }}.} In light of the examples given below , this makes sense: if you receive phone calls at an average rate of 2 per hour, then you can expect to wait half an hour for every call.en.wikipedia.org/wiki/Exponential_distribution - People also ask
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Jun 2, 2024 · It is the value \(m\) in the probability density function \(f(x) = me^{(-mx)}\) of an exponential random variable. It is also equal to \(m = \dfrac{1}{\mu}\), where \(\mu\) is the mean of the random variable.
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